DatriseAI-first ETL

1С:CRM Databricks SQL Warehouse

AI-first ETL from 1С:CRM into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads 1С:CRM into Databricks SQL Warehouse

Datrise syncs 1С:CRM's contacts, accounts, deals, activities, and lifecycle events into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

1С:CRM: CRM with strong adoption in CIS markets for sales and operations.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How 1С:CRM entities map to Databricks SQL Warehouse

1С:CRM entityDatabricks SQL Warehouse objectNotes
contacts1c_crm_contactsid PK · custom fields → VARIANT or STRUCT columns
accounts1c_crm_accountsid PK · linked to 1c_crm_contacts
deals1c_crm_dealsid PK · linked to 1c_crm_contacts
activities1c_crm_activitiesTIMESTAMP events

FAQ

How does Datrise handle 1С:CRM's custom fields in Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the 1С:CRM to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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